PERFICT: A Re-imagined foundation for predictive ecology.

Making predictions from ecological models-and comparing them to data-offers a coherent approach to evaluate model quality, regardless of model complexity or modelling paradigm. To date, our ability to use predictions for developing, validating, updating, integrating and applying models across scientific disciplines while influencing management decisions, policies, and the public has been hampered by disparate perspectives on prediction and inadequately integrated approaches. We present an updated foundation for Predictive Ecology based on seven principles applied to ecological modelling: make frequent Predictions, Evaluate models, make models Reusable, Freely accessible and Interoperable, built within Continuous workflows that are routinely Tested (PERFICT). We outline some benefits of working with these principles: accelerating science; linking with data science; and improving science-policy integration.

Improving carbon monitoring and reporting in forests using spatially-explicit information.

BACKGROUND: Understanding and quantifying carbon (C) exchanges between the biosphere and the atmosphere-specifically the process of C removal from the atmosphere, and how this process is changing-is the basis for developing appropriate adaptation and mitigation strategies for climate change. Monitoring forest systems and reporting on greenhouse gas (GHG) emissions and removals are now required components of international efforts aimed at mitigating rising atmospheric GHG. Spatially-explicit information about forests can improve the estimates of GHG emissions and removals. However, at present, remotely-sensed information on forest change is not commonly integrated into GHG reporting systems. New, detailed (30-m spatial resolution) forest change products derived from satellite time series informing on location, magnitude, and type of change, at an annual time step, have recently become available. Here we estimate the forest GHG balance using these new Landsat-based change data, a spatial forest inventory, and develop yield curves as inputs to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate GHG emissions and removals at a 30 m resolution for a 13 Mha pilot area in Saskatchewan, Canada. RESULTS: Our results depict the forests as cumulative C sink (17.98 Tg C or 0.64 Tg C year-1) between 1984 and 2012 with an average C density of 206.5 (±0.6) Mg C ha-1. Comparisons between our estimates and estimates from Canada's National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) were possible only on a subset of our study area. In our simulations the area was a C sink, while the official reporting simulations, it was a C source. Forest area and overall C stock estimates also differ between the two simulated estimates. CONCLUSIONS: Both estimates have similar uncertainties, but the spatially-explicit results we present here better quantify the potential improvement brought on by spatially-explicit modelling. We discuss the source of the differences between these estimates. This study represents an important first step towards the integration of spatially-explicit information into Canada's NFCMARS.

Accelerating forest growth enhancement due to climate and atmospheric changes in British Colombia, Canada over 1956-2001.

Changes in climate and atmospheric CO2 and nitrogen (N) over the last several decades have induced significant effects on forest carbon (C) cycling. However, contributions of individual factors are largely unknown because of the lack of long observational data and the undifferentiating between intrinsic factors and external forces in current ecosystem models. Using over four decades (1956-2001) of forest inventory data at 3432 permanent samples in maritime and boreal regions of British Columbia (B.C.), Canada, growth enhancements were reconstructed and partitioned into contributions of climate, CO2 and N after removal of age effects. We found that climate change contributed a particularly large amount (over 70%) of the accumulated growth enhancement, while the remaining was attributed to CO2 and N, respectively. We suggest that climate warming is contributing a widespread growth enhancement in B.C.'s forests, but ecosystem models should consider CO2 and N fertilization effects to fully explain inventory-based observations.

Simulations show decreasing carbon stocks and potential for carbon emissions in Rocky Mountain forests over the next century.

Climate change has altered the environment in which forests grow, and climate change models predict more severe alterations to come. Forests have already responded to these changes, and the future temperature and precipitation scenarios are of foremost concern, especially in the mountainous western United States, where forests occur in the dry environments that interface with grasslands. The objective of this study was to understand the trade-offs between temperature and water controls on these forested sites in the context of available climate projections. Three temperature and precipitation scenarios from IPCC AR4 AOGCMs ranging in precipitation levels were input to the process model Biome-BGC for key forested sites in the northern U.S. Rocky Mountains. Despite the omission of natural and human-caused disturbances in our simulations, our results show consequential effects from these conservative future temperature and precipitation scenarios. According to these projections, if future precipitation and temperatures are similar to or drier than the dry scenario depicted here, high-elevation forests on both the drier and wetter sites, which have in the absence of disturbance accumulated carbon, will reduce their carbon accumulation. Under the marginally drier climate projections, most forests became carbon sources by the end of the simulation horizon (2089). Under all three scenarios, growing season lengthened, the number of days with snow on the ground decreased, peak snow occurred earlier, and water stress increased through the projection horizon (1950-2089) for all sites, which represent the temperature and precipitation spectrum of forests in this region. The quantity, form, and timing of precipitation ultimately drive the carbon accumulation trajectory of forests in this region.